Channel state information feedback in wireless communication

ABSTRACT

Methods, systems, and devices for reducing channel state information feedback channel overhead by compressing coefficients of precoding vectors and reporting a subset of the compressed coefficients based on several parameters including network-signaled parameters. Some embodiments may be used in wireless communication embodiments in which channel state information from many layers and many frequency domain units need to be reported.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of International Patent ApplicationNo. PCT/CN2019/075146, filed on Feb. 15, 2019, the contents of which areincorporated herein by reference in their entirety.

TECHNICAL FIELD

This document is directed generally to wireless communications.

BACKGROUND

Wireless communication technologies are moving the world toward anincreasingly connected and networked society. A key enabler to meetingthe requirements of enhanced mobile broadband in the upcoming 5thGeneration (5G) New Radio (NR) networks is massive multi-inputmulti-output (MIMO) and beamforming techniques where multiple transmitantennas and/or multiple receive antennas are utilized in wirelessnodes. Using this, base-stations and user devices, can increase theperformance, efficiency, and reliability of the wireless communicationlink between them. Accurate estimation and reporting channel stateinformation (CSI) is important in such systems. However, the overhead ofreporting CSI increases as the number of utilized frequency band andtransmit/receive antennas increases which is particularly problematicgiven the large bandwidths and numerous spatial streams from manytransmit/receive antennas in 5G NR radio networks.

SUMMARY

This document relates to methods, systems, and devices for reducing theoverhead in reporting channel state information (CSI) such as precodingmatrix indicators by compressing the coefficients of precoding vectors.In some embodiments, reporting is performed using only a subset of thecompressed coefficients based on various criterion.

In one representative aspect, a wireless communication method of awireless communication device is disclosed. The method includesdetermining spatial basis vectors, and spatial basis vector coefficientswhere a precoding vector of the spatial channel is defined by a linearcombination of the spatial basis vectors and the spatial basis vectorcoefficients. The precoding vector is a vector that can be used topre-code a transmit data stream to mitigate impairments of the wirelesschannel. The method further includes compressing the spatial basisvector coefficients by determining frequency domain (FD) unit basisvectors and FD basis vector coefficients such that a combination of theFD basis vectors and the FD basis vector coefficients define the spatialbasis vector coefficients but at a reduced overhead. The wirelesscommunication device can then generate CSI (and a corresponding CSIfeedback report) based on the spatial basis vectors, the FD basisvectors, and the FD basis vector coefficients, among other parameters.

In another example aspect, a wireless communication apparatus comprisinga processor is disclosed. The processor is configured to implement theabove-described method.

In another example aspect, a computer program product is disclosed. Thecomputer program product includes a computer-readable medium that storesprocessor-executable instructions embodying the above-described method.

The above and other aspects and their implementations are described ingreater detail in the drawings, the descriptions, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an example of a base station (BS) and user equipment (UE)in wireless communication.

FIG. 2 shows a representative flow illustrating a method for compressingcoefficients of precoding vectors for determining CSI.

FIG. 3 shows an example block diagram illustrating a method forcompressing coefficients of precoding vectors.

FIG. 4 shows an example block diagram illustrating a method forcompressing coefficients of precoding vectors based on some constraints.

FIG. 5 is a block diagram representation of a portion of an apparatus.

DETAILED DESCRIPTION

There is an increasing demand for fourth generation of mobilecommunication technology (4G, the 4th Generation mobile communicationtechnology), Long-term evolution (LTE, Long-Term Evolution), andfifth-generation mobile communication technology (5G, the 5th Generationmobile communication technology) also called NR (New Radio).

In MIMO wireless communication systems, multiple antennas are used toperform signal transmissions. Such implementations include transmitterside processing, such as precoding or beamforming, to increasetransmission performance including efficiency and reliability. Toachieve high-performance precoding or beamforming, the precoding matrixor beamforming vector is selected to match the wireless channel. Thetransmitter therefore needs to determine the channel state information(CSI) to accurately pre-code or beamform the transmitted signal. Areceiver device can determine CSI based on received reference signals(e.g., CSI reference signals (CSI-RS), sounding reference signals (SRS),etc.) or pilots and then can report back the CSI to the transmitter(e.g., a UE can report the CSI to a BS). Accurate CSI feedback enableshigh-performance MIMO transmission.

However, the feedback of high-resolution CSI is costly in terms ofoverhead required in the feedback channel. This is especially the casewhen the transmitter needs CSI across multiple sub-bands (frequencysegments) or transmission layers (spatial streams). Theperformance-to-overhead trade-off of CSI feedback is a key metric torealizing the performance of high-resolution CSI.

In MIMO systems, the user device (e.g., user equipment (UE)) typicallyreports to a wireless node (e.g., a base station) the CSI which includesa precoding matrix indicator (PMI), a rank indicator (RI), and a channelquality indicator (CQI), among other parameters. RI indicates the numberof layers (which is related to the rank of the channel matrix), whereasPMI indicates a precoding vector. The precoding vector is used by thewireless node to pre-code each layer and is represented as a linearcombination of a set of spatial basis vectors. The UE quantizes (e.g.,converts to a digital representation) the amplitudes and phases of thecoefficients in the linear combination and the selected spatial basisvectors and reports the quantized values to the base station.

To allow for frequency-selective scheduling, for example, the quantizedphases and amplitudes are reported for each sub-band (or a subset of asub-band representing a frequency domain unit) if multiple sub-bands arecontained in the CSI reporting band. This high-resolution CSI feedbackresults in high performance MIMO transmission. However, for determiningor reporting CSI in multiple frequency domain units (or sub-bands) oracross multiple layers, the overhead can be quite large consuming alarge amount of resources in the feedback channel. Additionally, suchhigh-resolution CSI increases the UE's complexity and results in largerpower consumption. It is therefore beneficial to have a CSI reportingtechnique that provides for high-resolution CSI for multiple sub-bandsand/or layers, provides for high performance MIMO or beamforming, butwith a reduced CSI reporting overhead.

The present document uses section headings and sub-headings forfacilitating easy understanding and not for limiting the scope of thedisclosed techniques and embodiments to certain sections. Accordingly,embodiments disclosed in different sections can be used with each other.Furthermore, the present document uses examples from the 3GPP New Radio(NR) network architecture and 5G protocol only to facilitateunderstanding and the disclosed techniques and embodiments may bepracticed in other wireless systems that use different communicationprotocols than the 3GPP protocols.

FIG. 1 shows an example of a wireless communication system (e.g., anLTE, 5G or New Radio (NR) cellular network) that includes a BS 120 andone or more user equipment (UE) 111, 112 and 113. The uplinktransmissions (131, 132, 133) can include CSI feedback reports asdisclosed in this document. The UE may be, for example, a smartphone, atablet, a mobile computer, a machine to machine (M2M) device, aterminal, a mobile device, an Internet of Things (IoT) device, and soon.

FIG. 2 shows an example block diagram illustrating a method forcompressing coefficients of precoding vectors. At block 210, thewireless device (e.g., a UE) determines L spatial basis vectors [ν₁, ν₂,. . . , ν_(l), . . . , ν_(L)] for a spatial channel. In someembodiments, the L spatial basis vectors can be formed based on discreteFourier transform (DFT) vectors or Kronecker product of DFT vectors.

At block 220, the wireless device determines complex coefficients{a_(l,s) ^(r)} (i.e., coefficients having a magnitude and phase), wherel=1, 2, . . . , L are the number of spatial basis vectors, s=1, 2, . . ., S are the number of frequency domain (FD) units or sub-bands (i.e.,frequency segments over which CSI is to be reported), and r=1, 2, . . ., R are the layer indices for the rank-R spatial channel (i.e., thelayers of rank-R). The complex coefficients {a_(l,s) ^(r)} (writtensimply as {a}) are selected such that a combination (e.g., a linearcombination) of the complex coefficients {a} with the spatial basisvectors determines a precoding vector for the spatial channel over alllayers r∈{1, 2, . . . , R} and all FD units s∈{1, 2, . . . , S}. The UEcan determine the spatial basis vectors and the spatial basis vectorcoefficients from received reference signals or pilots transmitted by awireless node (e.g., a base station), for example, from CSI-RS (CSIReference Signals) with known amplitudes and phase offsets.

At block 230 and 240, the wireless device compresses the complexcoefficients {a} to reduce the overhead in reporting CSI to the basestation. At block 230 the UE determines M FD basis vectors {u_(l,1)^(r), . . . , u_(l,m) ^(r), . . . , u_(l,M) ^(r)} over L, and over allthe layers r of rank R, and at block 240 the UE determines complexcoefficients {c_(l,m) ^(r)} (written simply as {c}) over L, M and overall the layers r of rank R. The UE selects the FD basis vectors andcomplex coefficients {c} such that a combination of the FD basis vectorsand the complex coefficients {c} (e.g., a linear combination) determinesthe complex coefficients {a} of block 220. Furthermore, as describedfurther below, the network and the UE ensure that the number of bitsneeded to report the FD basis vectors and the complex coefficients {c}is lower than the number of bits needed to report {c} thus reducing theoverhead in CSI feedback reporting after the compression (for example,by the selection of M). Various techniques to further reduce thisoverhead are described below in relation to embodiments of the disclosedtechnology.

At block 250, the wireless device generates a CSI feedback report basedon, the spatial basis vectors, the FD basis vectors, the complexcoefficients {c}, and other additional parameters described below. Thatis, rather than reporting the complex coefficients {a}, the UE canreport, at a reduced overhead, the complex coefficients {c} along withthe FD basis vectors.

At block 260, the wireless device transmits the CSI feedback reports toa wireless node (e.g., to a base station in a physical uplink sharedchannel (PUSCH) or in a physical uplink control channel (PUCCH)). Thebase station can incorporate this feedback information into decisions onpre-coding or beamforming downlink data streams and generatingtransmission waveforms. In some embodiments, the wireless device can bea base station and can exclude the generation and transmission of a CSIfeedback report.

FIG. 3 shows a block diagram illustrating a method for compressingcoefficients of precoding vectors (e.g., MIMO precoding vectors, orbeamforming weights). Such precoding vectors can be used in, forexample, CSI feedback reports sent by UEs to base stations to supporthigh performance MIMO/beamforming transmissions.

1.0 Representative Embodiments for Compressing Precoding VectorCoefficients and Reporting a Subset of Coefficients for Each Layer

In some embodiments, user devices (e.g., UEs) report back to a wirelessnode (e.g., base stations) channel state information (CSI) in the formof a precoding matrix indicator (PMI). The PMI can be represented as alinear combination of spatial basis vectors over each layer r andfrequency domain (FD) units. For example, for L spatial basis vectors[ν₁, ν₂, . . . , ν_(L)], the precoding vector can be represented as:

$\begin{matrix}{f_{s}^{\; r} = {\left\lbrack {\nu_{1},\nu_{2},\ldots\mspace{14mu},\nu_{l},\ldots\mspace{14mu},\nu_{L}} \right\rbrack\begin{Bmatrix}a_{1,s}^{\; r} \\\vdots \\a_{l,s}^{\; r} \\\vdots \\a_{L,s}^{\; r}\end{Bmatrix}}} & \left( {{EQN}.\mspace{14mu} 1} \right)\end{matrix}$

where r is the layer index, s is the FD unit index, {ν₁, ν₂, . . . ,ν_(L)} are the L spatial basis vectors, and {a_(l,s) ^(r)} are thecoefficients of the precoding vector used to form the linear combinationwith the spatial basis vectors. In some embodiments, the L spatial basisvectors can be formed based on discrete Fourier transform (DFT) vectorsor Kronecker product of DFT vectors. The coefficients {a_(l,s) ^(r)} arecomplex variables including a magnitude and a phase and are quantized bythe user device and reported to the base station as part of the reportedCSI feedback. Because the coefficients {a_(l,s) ^(r)} can be differentfor different frequency domain units and/or layers, the overhead inreporting the quantized amplitudes and phases of {a_(l,s) ^(r)} can bequite large particular for large number of FD units (e.g., for widebandwidth divided into multiple small subbands or FD units where CSI isreported over all such FD units), and for a large number of layers(e.g., for massive MIMO systems with large number of transmit andreceive antennas over a full rank channel).

Therefore, in some representative embodiments, to reduce the overhead inreporting the quantized amplitudes and phases of {a_(l,s) ^(r)}, the UEcompresses the coefficients {a_(l,s) ^(r)} using a coefficientcompression module 350 as shown in FIG. 3. That is, for each layer r,the coefficient of spatial basic vector 1 (ν_(l)) across all the S FDunits (block 352 in FIG. 3) can be expressed as:

$\begin{matrix}{a_{l}^{r} = {\begin{bmatrix}a_{l,1}^{r} \\a_{l,2}^{r} \\\vdots \\a_{l,S}^{r}\end{bmatrix} = {\left\lbrack {u_{l,1}^{r},\ldots\mspace{14mu},u_{l,m}^{r},\ldots\mspace{14mu},u_{l,M}^{r}} \right\rbrack\begin{bmatrix}c_{l,1}^{r} \\\vdots \\c_{l,m}^{r} \\\vdots \\c_{l,M}^{r}\end{bmatrix}}}} & \left( {{EQN}.\mspace{14mu} 2} \right)\end{matrix}$

where {u_(l,1) ^(r), . . . , u_(l,M) ^(r)} (block 354 in FIG. 3) are theM length-N3 FD basis vectors, and c_(l,m) ^(r) in block 356 is thecoefficient for beam 1 and FD basis vector m after compression by thecoefficient compression module 350. The coefficient compression module350 can generate the FD basis vector {u_(l,1) ^(r), . . . , u_(l,M)^(r)} based on DFT vectors.

Before compression, the precoder FD unit 1 (block 310) generates aprecoding vector f₁ ^(r); (output 312) for the first FD unit and a layerr, as a linear combination of the spatial basic vectors [ν₁, ν₂, . . . ,ν_(l), . . . , ν_(L)] (block 314) and the coefficients {a_(l,1) ^(r)}(block 316). This can be expressed as:

$\begin{matrix}{f_{1}^{r} = {\left\lbrack {v_{1},v_{2},\ldots\mspace{14mu},v_{l},\ldots\mspace{14mu},v_{L}} \right\rbrack\begin{bmatrix}a_{1,1}^{r} \\\vdots \\a_{l,1}^{r} \\\vdots \\a_{L,1}^{r}\end{bmatrix}}} & \left( {{EQN}.\mspace{14mu} 3} \right)\end{matrix}$

Similarly, the precoder FD unit 2 (block 320) generates a precodingvector f₂ ^(r) for the second FD unit and a layer r, as a linearcombination of the spatial basic vectors [ν₁, ν₂, . . . , ν₁, . . . ,ν_(l)] and the coefficients {a_(l,2) ^(r)} (block 326) which can beexpressed as:

$\begin{matrix}{f_{2}^{r} = {\left\lbrack {v_{1},v_{2},\ldots\mspace{14mu},v_{l},\ldots\mspace{14mu},v_{L}} \right\rbrack\begin{bmatrix}a_{1,2}^{r} \\\vdots \\a_{l,2}^{r} \\\vdots \\a_{L,2}^{r}\end{bmatrix}}} & \left( {{EQN}.\mspace{14mu} 4} \right)\end{matrix}$

The S-th precoder FD unit (block 330) generates a precoding vector asexpressed by:

$\begin{matrix}{f_{S}^{r} = {\left\lbrack {v_{1},v_{2},\ldots\mspace{14mu},v_{l},\ldots\mspace{14mu},v_{L}} \right\rbrack\begin{bmatrix}a_{1,S}^{r} \\\vdots \\a_{l,S}^{r} \\\vdots \\a_{L,S}^{r}\end{bmatrix}}} & \left( {{EQN}.\mspace{14mu} 5} \right)\end{matrix}$

In some embodiments, the UE reports the FD basic vector {u_(l,1) ^(r), .. . , u_(l,m) ^(r), . . . , u_(l,m) ^(r)} (block 354), and thecoefficients of the FB basis vector {c_(l,m) ^(r)} (block 356),generated by the coefficient compression module 350 instead of reportingthe coefficients {a_(l,s) ^(r)}. Because of the correlation of thecoefficients {a_(l,s) ^(r)} before compression, M can be set to besmaller than 2 L resulting in a lower overhead in transmitting the FDbasis vectors {u_(l,1) ^(r), . . . , u_(l,M) ^(r)} and the coefficients{c_(l,m) ^(r)} relative to the overhead in transmitting the uncompressedcoefficients {a_(l,s) ^(r)}. A benefit from the compression can beachieved for M<S.

In some embodiments, the overhead in reporting the L*M coefficients{c_(l,m) ^(r)} can be further reduced, for example, by selecting, foreach layer, K0 subset of the L*M coefficients. That is, the number ofnon-zero coefficients is constrained to be no larger than K0 (i.e., anupper bound for the number of coefficients in the subset is K0), and theUE reports the location or position of the K1 non-zero coefficients inthe L*M coefficients, and the amplitudes and phases of the K1coefficients.

In some embodiments, the value of M can be based on N3 values and/ornetwork-configured parameters (e.g., N3=S). For example, M=ceil(pN₃),where p is based on network configured parameters, and M is the leastinteger greater than or equal to the product of p and the N3 value(ceiling function) (ceil(x)=least integer greater than or equal to x).In other embodiments, M can be constrained by other parametersconfigured in the UE or derived by the UE.

In some embodiments, the UE or the network can set the value of K0 todepend on L, M, and/or parameters configured by the network. Forexample, K0 can be set to K0=ceil(βLM), where β can be based onconfigured parameters.

2.0 Representative Embodiments for Constraining the Overhead forReporting CSI

In some embodiments, CSI can be divided into two parts, for example aCSI part 1 and a CSI part 2. In CSI part 1, the UE can report a channelquality indicator (CQI), a rank indicator (RI), and a value indicatingthe number of non-zero coefficients ({c_(l,m) ^(r)}) across a number oflayers (e.g., across R layers, wherein R is the rank value), among otherparameters. The bit width of the indication of the number of non-zerocoefficients across a number of layers can be determined by a maximumnumber of layers. The maximum number of layers can be determined by themaximum rank that a codebook can support (for codebook-based precoding),a network configuration parameter, a capability value that the UEreports to the base station, etc. In CSI part 2, the UE reports otherCSI parameters such as a precoding matrix indicator (PMI). The reportedPMI can include an indicator for the spatial basis vectors (e.g.,vectors 314 in FIG. 3), an indicator for the FD basis vectors (e.g.,vectors 354), an indicator for the amplitude and phase of the compressedcoefficients (e.g., coefficients 356), and an indication of the locationof the non-zero coefficients in the L*M coefficients.

In some embodiments, CSI parameters in each part are jointly channelcoded, but different parts are channel-coded independently.Additionally, the payload of CSI part 2 can depend on the value of CSIpart 1 so that the network need not always reserve the maximum overheadfor CSI transmission. That is, CSI part 1 can have a fixed allocationand can contain parameters that always need to be fed back, and CSI part2 can include parameters that may not always need to be fed back or thatcan have variable size (e.g., variable bit width). Using this approach,when CSI part 2 does not utilize the maximum possible overhead, theunused overhead is saved from allocation leading to higher efficiency.For example, if the maximum number of layers that the UE reports in acapability value is R1 (i.e., UE capable of processing up to only R1layers), and the number of coefficients to report per layer isconstrained to K0, the minimum bits required to report K0*R1 non-zerocoefficients is ceil(log₂ (R1×K0)). Alternatively, if the maximum numberof layers is limited by a network configuration parameter to R2 (e.g.,based on a parameter limiting the RI values that the UE can report), theminimum bits to report K0*R2 non-zero coefficients is ceil(log₂(R2×K0)). Alternatively, if the number of RI values that the codebook inuse can support is R3, the minimum bits to report R3*K0 non-zerocoefficient ceil(log₂ (R3×K0)). In some embodiments, when the UE hasmultiple constraints on the number or layers (e.g., number of layersconstrained by two or more of R1, R2, or R3) the bit-width to report thenon-zero coefficients can be set to ceil(log₂ (R4×K0)), where R4 is theminimum of {R1, R2, R3}.

3.0 Representative Embodiments for Constraining the Overhead forReporting CSI for Large Ranks

As the number of compressed coefficients {c_(l,m) ^(r)} (e.g., block 356in FIG. 3) increases with increasing number of layers R, (e.g., as therank of the spatial channel increases), the CSI overhead likewiseincreases. Therefore, in some embodiments, the number of spatial basisvectors (e.g., vectors 314), the number of FD basis vectors (e.g.,vectors 354), or the number of coefficients in the K0 subset of the L*Mcoefficients can be constrained to not grow too much with increased R(or to grow at a lower rate), e.g., to be the same when R is large aswhen R is small.

For a rank-R CSI report, if the rank, R, is selected from a candidateset S1 of rank values, the bit width to report the non-zero coefficientsdepends on the maximum number of coefficients in the K0-subset that canbe reported across all the layers for any of the rank values in thecandidate set S1. For example, if a rank R_(max) in S1 would yield themaximum number of coefficients in the K0-subset across all the layers,the bit width for reporting the non-zero coefficients can be as large asceil(log₂ (R_(max)×K0)). That is, the bit width for reporting thenon-zero coefficients is ceil(log₂ (max({S1})×K0)), where max({S1}) isthe rank (R_(max)) in S1 yielding the maximum number of coefficients inthe K0-subset. In some embodiments, the candidate set S1 can bedetermined by a network configuration parameter and/or a capabilityvalue that UE reports.

In some embodiments, the total number of spatial basis vectors of allthe R layers for a rank-R CSI report, can be constrained to be less thanor equal to the total number of spatial basis vectors of all the R0layers for a rank-RO CSI report, where R>R0≥1. Additionally, in someembodiments, the bit width used to report the number of non-zerocoefficients in CSI part 1 can be based on the number of spatial basisvectors in each layer when the rank is R0. For example, the bit widthcan be constrained to ceil(log₂ (R0×ceil(β×M*2L*R0))), where L*R0 is thenumber of spatial basis vectors in each layer when the rank is R0.

In some embodiments, the total number of FD basis vectors of all the Rlayers for a rank-R CSI report, can be constrained to be less than orequal to the total number of FD basis vectors of all the R0 layers for arank-RO CSI report, where R>R0≥1. Additionally, in some embodiments, thebit width used to report the number of non-zero coefficients in CSI part1 can be based on the number of FD basis vectors in each layer when therank is R0. For example, the bit width can be constrained to ceil(log₂(R0×ceil(β×M*2L*R0))), where M*R0 is the number of FD basis vectors ineach layer when the rank is R0.

In some embodiments, the total number of coefficients in the K0-subsetof all the R layers can be constrained to be less than or equal to thetotal number of coefficients in the K0-subset of all the R0 layers for arank-RO CSI report, where R>R0≥1. Additionally, in some embodiments, thebit width used to report the number of non-zero coefficients in CSI part1 can be based on the K0 value when the rank is R0. For example, the bitwidth can be constrained to ceil(log₂ (R0×K0*R0)), where K0*R0 is K0value in each layer when the rank is R0.

3.1 Representative Embodiments for Constraining the Number of FD BasisVectors Per Layer, or the K0 Value Per Layer, for Larger Ranks to be aPredetermined Fraction of the Values for Lower Ranks:

In some embodiments, the number of FD basis vectors for each layer for arank-R CSI report can depend on the value of the rank, R. For example,if for ranks less than or equal to 2, the number of FD basis vectors foreach layer is M0, the number of FD basis vectors per layer for any rankR>2 can be set to

$M = {{{floor}\left( {\frac{2}{R}M\; 0} \right)}.}$

That is, M can be set to the greatest integer less than or equal to

$\frac{2}{R}*M\; 0{\left( {{{floor}(x)} = {{greatest}\mspace{14mu}{integer}\mspace{14mu}{less}\mspace{14mu}{than}\mspace{14mu}{or}\mspace{14mu}{equal}\mspace{14mu}{to}\mspace{14mu} x}} \right).}$

In some embodiments, a range of ranks can be constrained such that thetotal number of FD basis vectors remains constant for ranks within therange. For example, if the number of FD basis vectors per layer forrank-2 is M0, the number of FD basis vectors per layer for rank-3 andrank-4 can be constrained to

$M = {{{floor}\left( {\frac{1}{2}M\; 0} \right)}.}$

Thus, a rank-4 CSI report would have the same total number of FD basisvectors as a rank-2 CSI report.

In some embodiments, the K0 value can be based on the rank value. Forexample, if the K0 value for ranks less than or equal to 2 is K0₁, theK0 value for rank-R (R>2) can be set to

${K\; 0} = {{{floor}\left( {\frac{2}{R}K\; 0_{1}} \right)}.}$

In some embodiments, a range of ranks can be constrained to have thesame fraction of K0 values per layer as a specified lower rank K0 value.For example, if ranks less than or equal to 2 have a K0 value of K0₁,rank-3 and rank-4 can be constrained to have a K0 value of

${{floor}\left( {\frac{1}{2}K\; 0_{1}} \right)}.$

3.2 Representative Embodiments for Constraining the Number of SpatialBasis Vectors Per Layer, the Number of FD Basis Vectors Per Layer, andthe K0 Value Per Layer Based on a Maximum Rank Riven by NetworkConfiguration Parameters:

In some embodiments, for a rank-R CSI report, the number of FD basisvectors for each layer can be based on a maximum rank value given by anetwork configuration parameter. For example, if the number of FD basisvectors for each layer for ranks less than or equal to 2 is M0, thenumber of FD basis vectors per layer for ranks greater than 2 can be setto

${M = {{floor}\left( {\frac{2}{R\_ cfg}M\; 0} \right)}},$

where R_cfg is the maximum rank value given by the network configurationparameter.

In some embodiments, for a rank-R CSI report, the K0 value of each layercan be based on a maximum rank value given by a network configurationparameter. For example, if the K0 value for each layer for ranks lessthan or equal to 2 is K0₁, the K0 value for each layer for ranks greaterthan 2 can be set to

${{K\; 0} = {{floor}\left( {\frac{2}{R\_ cfg}K\; 0_{1}} \right)}},$

where R_cfg is the maximum rank value given by the network configurationparameter.

In some embodiments, for a rank-R CSI report, the number of spatialbasis vectors for each layer can be based on a maximum rank value givenby a network configuration parameter. For example, if the number ofspatial basis vectors for each layer for ranks less than or equal to 2is L0, the number of spatial basis vectors per layer for ranks greaterthan 2 can be set to

${L = {{floor}\left( {\frac{2}{R\_ cfg}L\; 0} \right)}},$

where R_cfg is the maximum rank value given by the network configurationparameter.

3.3 Representative Embodiments for Constraining the Number of SpatialBasis Vectors Per Layer, the Number of FD Basis Vectors Per Layer, andthe K0 Value Per Layer Based on A UE Capability:

In some embodiments, for a rank-R CSI report, the number of FD basisvectors for each layer depends on a maximum rank value that the UE cansupport or that the UE reports in a capability parameter (i.e., UEcapability value). For example, if the number of FD basis vectors foreach layer for ranks less than or equal to 2 is M0, the number of FDbasis vectors per layer for ranks greater than 2 can be set to

${M = {{floor}\left( {\frac{2}{R\_ UE}M\; 0} \right)}},$

where R_UE is the maximum rank value given by the UE capability value.

In some embodiments, for a rank-R CSI report, the K0 value of each layercan be based on a reported UE capability value. For example, if the K0value for each layer for ranks less than or equal to 2 is K0₁, the K0value for each layer for ranks greater than 2 can be set to

${{K\; 0} = {{floor}\left( {\frac{2}{R\_ UE}K\; 0_{1}} \right)}},$

where R_UE is the maximum rank value given by the UE capability value.

In some embodiments, for a rank-R CSI report, the number of spatialbasis vectors for each layer can be based on a reported UE capabilityvalue. For example, if the number of spatial basis vectors for eachlayer for ranks less than or equal to 2 is L0, the number of spatialbasis vectors per layer for ranks greater than 2 can be set to

${L = {{floor}\left( {\frac{2}{R\_ UE}L\; 0} \right)}},$

where R_UE is the maximum rank value given by the UE capability value.

FIG. 4 shows a block diagram illustrating a method for compressingcoefficients of precoding vectors where M is set equal to 2 L. That iseach of the 2 L coefficients (e.g., coefficients 416, 426, and 436) foreach FD units (a total of S*2 L coefficients over all S FD units) arecompressed to M*2 L coefficients (for each rank) by a coefficientcompression module 450. This compression can be realized by decomposingthe spatial basis vector coefficients (e.g., coefficients 452) into alinear combination of the FD basis vector coefficients (e.g.,coefficients 456) and the FD basis vectors (e.g., vectors 454).

Some example embodiments may be described using the following clauses.

Clause 1. A wireless device (e.g., UE) generates a channel stateinformation (CSI) based at least in part on a first plurality of L basisvectors (e.g., spatial basis vectors), a second plurality of M basisvectors (e.g., FD basis vectors) and a plurality of coefficients (e.g.,coefficients for FD basis vectors), wherein the first plurality of basisvectors, the second plurality of basis vectors and the plurality ofcoefficients are indicate information regarding a precoding vector(i.e., the basis vectors and coefficients are selected to provide to awireless node, e.g., a base station, information regarding the channelso that the wireless node can utilize this information in precodingdownlink data streams). In some embodiments, the wireless device candetermine the first plurality of basis vectors (e.g., spatial basisvectors) and/or the second plurality of basis vectors (e.g., FD basisvectors) by selecting the basis vectors from a set of basis vectorsprovided in one or more code books. That is, the wireless can determinewhich basis vectors from the predefined set of basis vectors in thecodebook matches closest with a basis vector required to accuratelyestimate the wireless channel. When the wireless device is a UE, it cangenerate a CSI report based on the CSI and generate a transmissionwaveform based on the CSI report and transmit it to a base station(e.g., in a physical uplink control channel (PUCCH) or a physical uplinkshared channel (PUSCH)). Additional details are provided in section 1.0above.

Clause 2. For each layer r in a plurality of R layers, selecting asubset with less than or equal to K0 non-zero coefficients from theplurality of coefficients and generating the CSI based, at least inpart, on the first plurality of basis vectors, the second plurality ofbasis vectors, and the subset of non-zero coefficients for each of thelayers r in the plurality of R layers. Additional details are providedin section 1.0 above.

Clause 3. Generating a first part of the CSI (or a first part of the CSIfeedback report), The first part includes, for example, a channelquality indicator (CQI), a rank indicator (RI), and an indication of anumber of non-zero coefficients across the R layers (R is a rank value).

Clause 4. Generating a second part of the CSI (or CSI feedback report),where the second part includes, for example, a precoding matrixindicator (PMI). Additional details are provided in section 2.0 above.

Clause 5. The PMI includes an indication of the first plurality of Lbasis vectors, an indication of the second plurality of M basis vectors,an indication of an amplitude and a phase of the plurality ofcoefficients, and an indication of locations of non-zero coefficients ofthe plurality of coefficients (e.g., the L*M plurality of coefficientsin each layer r of R). Additional details are provided in section 2.0above.

Clause 6. One or more CSI parameters within the first part of the CSI(or CSI feedback report) are jointly channel coded, one or more CSIparameters within the second part are also jointly channel coded, andthe first part is channel coded independent of the second part (i.e.,CSI parameters in each part are jointly channel coded, whereas differentparts are channel-coded independently). Additional details are providedin section 2.0 above.

Clause 7. Constraining at least one of L, M, and K0 to cause, when arank R is larger than a rank R0, the K0 value for rank R to be less thanor equal to the K0 value for rank R0 (R>R0≥1). Additional details areprovided in section 2.0 above.

Clause 8. Constraining at least one of L, M, and K0 to cause, when arank R is larger than a rank R0, the K0 value for the rank R to be apredetermined fraction of the K0 value for the rank R0, wherein R0 isgreater than or equal to one. Additional details are provided in section2.0 above.

Clause 9. When R>R0≥1, the total number of coefficients in the subset ofall the R layers is equal to or smaller than the total number ofcoefficients in the subset of all the R0 layers in the rank-R0 CSI. Thebit width of the indication of number of non-zero coefficients dependson the L/M/K0 value when rank is R0 as well as the value of R0. As aresult, although the indication of number of non-zero coefficients meansthe number of non-zero coefficients across a maximum number of layers,the bit width of this indication can depend on just a smaller number ofrank value, e.g., R0. Additionally, in some embodiments, K0 depends onthe value of L and M (e.g., K0=p*L*M). Hence, in some embodiments K0 canbe constrained by constraining L, M, or other parameters used todetermine K0 (e.g., p). K0 represents an upper bound of the number ofnon-zero coefficients. Additional details are provided in sections 2.0and 3.0 above.

Clause 10. At least one of L, M, and K0 can be constrained based on amaximum allowed number of layers, where the maximum allowed number oflayers is based on, for example, a network configuration parameter, acapability of the wireless device, a maximum rank that a code book usedto determine the precoding vector can support, etc. Additional detailsare provided in section 3.0 above.

Clause 11. The wireless device can be a UE or a BS. That is, in someembodiments, a UE or a BS can generate CSI according to any of theclauses above. Additionally, or alternatively, a UE can generate the CSIreport and send it to a wireless node (e.g., a BS). When the BS receivesa CSI feedback report from the UE, the CSI feedback report would havebeen generated according to one or more of the clauses above. That is,the BS receives the first plurality of L basis vectors, the secondplurality of M basis vectors, and the plurality of coefficients.Additionally, the CSI feedback report includes a first part and a secondpart as described above. In some embodiments, the BS can merely receivean indication of what the basis vectors and coefficients are withoutreceiving the actual vectors (for example, the BS can receive anindication of a codebook index relating to corresponding basis vectorsor look up the actual coefficients from a lookup table using thereceived indication of coefficients). Additionally, the BS need notalways receive the second part of the CSI report (or need not receivethe maximum number of bits that can be associated with the second part).Instead, the BS can allocate a variable number of resources to receivethe second part based on the payload received in the first part of theCSI report further reducing the overhead of reporting CSI. The BS canuse (but need not use) the received information to generate a precodingvector to precode downlink data streams and generates a downlinktransmission waveform based on the precoded data.

The wireless device (e.g., UE) or wireless node (e.g., base station) caninclude a processor configured to implement a method recited in any oneor more of clauses above. Additionally, the UE or base station caninclude a computer program product comprising a computer-readableprogram medium having processor executable instructions stored thereon,the instructions, when executed by a processor, causing the processor toimplement a method recited in any one or more of the clauses above.

FIG. 5 is a block diagram representation of a portion of an apparatus,in accordance with some embodiments of the presently disclosedtechnology. An apparatus 505, such as a base station or a wirelessdevice (or UE), can include processor electronics 510 such as amicroprocessor that implements one or more of the techniques presentedin this document. The apparatus 505 can include transceiver electronics515 to send and/or receive wireless signals over one or morecommunication interfaces such as antennas 520 and 522. The apparatus 505can include other communication interfaces for transmitting andreceiving data. Apparatus 505 can include one or more memories (notexplicitly shown) configured to store information such as data and/orinstructions. In some implementations, the processor electronics 510 caninclude at least a portion of the transceiver electronics 515. In someembodiments, at least some of the disclosed techniques, modules orfunctions are implemented using the apparatus 505.

It is intended that the specification, together with the drawings, beconsidered exemplary only, where exemplary means an example and, unlessotherwise stated, does not imply an ideal or a preferred embodiment. Asused herein, the use of “or” is intended to include “and/or”, unless thecontext clearly indicates otherwise.

Some of the embodiments described herein are described in the generalcontext of methods or processes, which may be implemented in oneembodiment by a computer program product, embodied in acomputer-readable medium, including computer-executable instructions,such as program code, executed by computers in networked environments. Acomputer-readable medium may include removable and non-removable storagedevices including, but not limited to, Read Only Memory (ROM), RandomAccess Memory (RAM), compact discs (CDs), digital versatile discs (DVD),etc. Therefore, the computer-readable media can include a non-transitorystorage media. Generally, program modules may include routines,programs, objects, components, data structures, etc. that performparticular tasks or implement particular abstract data types. Computer-or processor-executable instructions, associated data structures, andprogram modules represent examples of program code for executing stepsof the methods disclosed herein. The particular sequence of suchexecutable instructions or associated data structures representsexamples of corresponding acts for implementing the functions describedin such steps or processes.

Some of the disclosed embodiments can be implemented as devices ormodules using hardware circuits, software, or combinations thereof. Forexample, a hardware circuit implementation can include discrete analogand/or digital components that are, for example, integrated as part of aprinted circuit board. Alternatively, or additionally, the disclosedcomponents or modules can be implemented as an Application SpecificIntegrated Circuit (ASIC) and/or as a Field Programmable Gate Array(FPGA) device. Some implementations may additionally or alternativelyinclude a digital signal processor (DSP) that is a specializedmicroprocessor with an architecture optimized for the operational needsof digital signal processing associated with the disclosedfunctionalities of this application. Similarly, the various componentsor sub-components within each module may be implemented in software,hardware or firmware. The connectivity between the modules and/orcomponents within the modules may be provided using any one of theconnectivity methods and media that is known in the art, including, butnot limited to, communications over the Internet, wired, or wirelessnetworks using the appropriate protocols.

While this document contains many specifics, these should not beconstrued as limitations on the scope of an invention that is claimed orof what may be claimed, but rather as descriptions of features specificto particular embodiments. Certain features that are described in thisdocument in the context of separate embodiments can also be implementedin combination in a single embodiment. Conversely, various features thatare described in the context of a single embodiment can also beimplemented in multiple embodiments separately or in any suitablesub-combination. Moreover, although features may be described above asacting in certain combinations and even initially claimed as such, oneor more features from a claimed combination can in some cases be excisedfrom the combination, and the claimed combination may be directed to asub-combination or a variation of a sub-combination. Similarly, whileoperations are depicted in the drawings in a particular order, thisshould not be understood as requiring that such operations be performedin the particular order shown or in sequential order, or that allillustrated operations be performed, to achieve desirable results.

Only a few implementations and examples are described and otherimplementations, enhancements and variations can be made based on whatis described and illustrated in this disclosure.

1-31. (canceled)
 32. A method for wireless communication, comprising:generating, by a wireless device, a channel state information (CSI)feedback report, wherein a first part of the CSI feedback reportincludes a channel quality indicator (CQI), a rank indicator (RI), andan indication of a number of non-zero coefficients across a plurality oflayers, wherein a second part of the CSI feedback report includes aprecoding matrix indicator (PMI) determined based on a first pluralityof L basis vectors, a second plurality of M basis vectors, and a numberof non-zero coefficients for each layer of the plurality of layers,wherein the number of non-zero coefficients for each layer is smallerthan or equal to K₀ non-zero coefficients, wherein K₀ is determinedbased on at least one of L or M, wherein L, M, and K₀ are integers; andtransmitting, by the wireless device, the CSI feedback report to awireless node.
 33. The method of claim 32, wherein a bit width of theindication of the number of non-zero coefficients across the pluralityof layers is based on K₀.
 34. The method of claim 32, wherein a bitwidth of the indication of the number of non-zero coefficients acrossthe plurality of layers is based on a maximum number of layers.
 35. Themethod of claim 34, wherein a bit width of the indication of the numberof non-zero coefficients across the plurality of layers is based on K₀.36. The method of claim 32, wherein a value of K₀ for a layer of rank Ris equal to the value of K₀ for a layer of rank R₀, wherein R>R₀, andwherein R₀ is greater than or equal to
 1. 37. The method of claim 32,wherein at least one of L, M, or K₀ is based on a network configurationparameter.
 38. A method for wireless communication, comprising:receiving, by a wireless node, a channel state information (CSI)feedback report from a wireless device, wherein a first part of the CSIfeedback report includes a channel quality indicator (CQI), a rankindicator (RI), and an indication of a number of non-zero coefficientsacross a plurality of layers, wherein a second part of the CSI feedbackreport includes a precoding matrix indicator (PMI) determined based on afirst plurality of L basis vectors, a second plurality of M basisvectors, and a number of non-zero coefficients for each layer of theplurality of layers, wherein the number of non-zero coefficients foreach layer is smaller than or equal to K₀ non-zero coefficients, whereinK₀ is determined based on at least one of L or M, and wherein L, M, andK₀ are integers.
 39. The method of claim 38, wherein a bit width of theindication of the number of non-zero coefficients across the pluralityof layers is based on K₀.
 40. The method of claim 38, wherein a bitwidth of the indication of the number of non-zero coefficients acrossthe plurality of layers is based on a maximum number of layers.
 41. Themethod of claim 40, wherein a bit width of the indication of the numberof non-zero coefficients across the plurality of layers is based on K₀.42. The method of claim 38, wherein a value of K₀ for a layer of rank Ris equal to the value of K₀ for a layer of rank R₀, wherein R>R₀, andwherein R₀ is greater than or equal to
 1. 43. The method of claim 38,wherein at least one of L, M, or K₀ is based on a network configurationparameter.
 44. A device for wireless communication, comprising aprocessor configured to: generate a channel state information (CSI)feedback report, wherein a first part of the CSI feedback reportincludes a channel quality indicator (CQI), a rank indicator (RI), andan indication of a number of non-zero coefficients across a plurality oflayers; wherein a second part of the CSI feedback report includes aprecoding matrix indicator (PMI) indicating a precoding matrixdetermined based on a first plurality of L basis vectors, a secondplurality of M basis vectors, and a number of non-zero coefficients foreach layer of the plurality of layers, wherein the number of non-zerocoefficients for each layer is smaller than or equal to K₀ non-zerocoefficients, wherein K₀ is determined based on at least one of L or M,wherein L, M, and K₀ are integers; and transmit the CSI feedback reportto a wireless node.
 45. The device of claim 44, wherein a bit width ofthe indication of the number of non-zero coefficients across theplurality of layers is based on K₀.
 46. The device of claim 44, whereina bit width of the indication of the number of non-zero coefficientsacross the plurality of layers is based on a maximum number of layers.47. The device of claim 46, wherein a bit width of the indication of thenumber of non-zero coefficients across the plurality of layers is basedon K₀.
 48. The device of claim 44, wherein a value of K₀ for a layer ofrank R is equal to the value of K₀ for a layer of rank R₀, wherein R>R₀,and wherein R₀ is greater than or equal to
 1. 49. The device of claim44, wherein at least one of L, M, or K₀ is based on a networkconfiguration parameter.
 50. A device for wireless communication,comprising a processor configured to: receive a channel stateinformation (CSI) feedback report from a wireless device, wherein afirst part of the CSI feedback report includes a channel qualityindicator (CQI), a rank indicator (RI), and an indication of a number ofnon-zero coefficients across a plurality of layers, and wherein a secondpart of the CSI feedback report includes a precoding matrix indicator(PMI) indicating a precoding matrix determined based on a firstplurality of L basis vectors, a second plurality of M basis vectors, anda number of non-zero coefficients for each layer of the plurality oflayers, wherein the number of non-zero coefficients for each layer issmaller than or equal to K₀ non-zero coefficients, wherein K₀ isdetermined based on at least one of L or M, and wherein L, M, and K₀ areintegers.
 51. The device of claim 50, wherein a bit width of theindication of the number of non-zero coefficients across the pluralityof layers is based on K₀.
 52. The device of claim 50, wherein a bitwidth of the indication of the number of non-zero coefficients acrossthe plurality of layers is based on a maximum number of layers.
 53. Thedevice of claim 52, wherein a bit width of the indication of the numberof non-zero coefficients across the plurality of layers is based on K₀.54. The device of claim 50, wherein a value of K₀ for a layer of rank Ris equal to the value of K₀ for a layer of rank R₀, wherein R>R₀, andwherein R₀ is greater than or equal to
 1. 55. The device of claim 50,wherein at least one of L, M, or K₀ is based on a network configurationparameter.